Healthcare faces significant challenges due to fragmented data, vendor-locked systems, and security concerns, which hinder the timely delivery of clinical insights and efficient workflow management. This book explores the transformative potential of AI, particularly deep learning (DL) AI, in addressing these issues and enabling personalized healthcare. It covers diverse applications such as clinical trials, telemedicine, EHR management, and disease detection, emphasizing the importance of accurate algorithms to enhance patient outcomes. Key chapters delve into AI's impact on areas like Parkinson's and Alzheimer's detection, the role of blockchain in data integrity, the use of NLP, AR/VR in healthcare, and strategies to combat billing fraud. The book also highlights the importance of diversity in healthcare and presents cutting-edge DL frameworks, such as YOLOv8 and U-Net, for medical image segmentation, offering valuable insights for researchers, practitioners, and policymakers alike.